The 2014 decline in oil prices lowered short-run inflation. Before the Global Crisis, the medium-term correlation between oil prices and inflation was weak, but it has become much stronger since the onset of the Crisis. This column suggests that following the onset of the Crisis, inflation expectations reacted quite strongly to global demand conditions and oil supply shocks. The public’s belief in the ability of monetary authorities to stabilise inflation at the medium-term horizon has deteriorated.

The sharp decline in oil prices starting in late 2014 sparked a debate about their effect on inflation and the world economy (e.g. World Bank 2015). The decline in oil prices lowered inflation in the short run, and in some cases pushed some economies that were already experiencing very low inflation into deflation. More surprisingly, data from the US, the Eurozone, the UK, and Israel show that oil prices have a strong correlation with inflation expectations for the medium term, as measured by five-year breakeven inflation rates.1 Before the Global Crisis, this correlation was weaker and expectations were firmly anchored at the 2% level. However, from the onset of the Global Crisis, the correlation has been quite high (Table 1 and Figure 1).

In this column, we decompose the change in oil prices to global demand and supply shocks. Using this decomposition we show that following the onset of the Crisis, inflation expectations reacted quite strongly to global demand conditions and oil supply shocks. These findings suggest that the public’s belief in the ability of monetary authorities to stabilise inflation at the medium-term horizon has deteriorated. This could be due to:

Decomposing oil prices changes

The effect of oil prices on five-year breakeven inflation expectations is surprising since oil-related products make up a small fraction of the CPI. One possibility is that oil prices affect production costs of many goods and, therefore, there is a strong and relatively quick pass-through from oil prices to the general price level. Another possibility is that global aggregate demand affects both the prices of oil and prices of other goods such that we observe a ‘spuriously’ high correlation between oil prices and inflation expectations. Any combination of these explanations is also possible.

Note: For the Eurozone, we used a GDP-weighted average of separately estimated breakeven rates for France and Germany.Source: Bloomberg and the Bank of Israel.

We exploit the fact that a large number of commodities’ contracts are traded in financial markets. While each commodity is affected by idiosyncratic supply and demand shocks, they are also affected by common ‘global demand' shocks. In fact, in the period we examine – 2000 to 2015 – the correlation between the main commodity indices, oil, metals, and agricultural goods, is above 40% (Figure 2 and Table 2).2

We extract the first principal component of the three indices – a factor that accounts for 70% of their common variation. We plot the first principal component and find that it tracks very well global economic activity (Figure 3).3,4 Focusing on the latest data points, we learn that global demand is decelerating. Therefore, part of the recent decline in oil prices reflects a slowing down of the world economy.

Figure 3. Co-movement of major commodity indices. First principal component of annual rates of change in prices of oil, metals, and agricultural commodities (monthly, 2001M1-2015M6)

Source: Bloomberg and authors' calculations.

The economic press, however, focused on dramatic developments on the supply side of oil production, namely, increased competition from alternative energy sources. We use the commodity indices data to test this hypothesis. We regress oil prices on the indices of metals and agricultural commodities, controlling for weather conditions in the US and major agricultural producing countries in Latin America (Figure 4). The residuals from the equation capture the idiosyncratic shocks to oil prices. 5,6 We find highly negative residuals between November 2014 and June 2015 when oil prices fell significantly more than other commodities.

This suggests that the world economy faced a significant positive supply shock (in addition to the common negative demand shock).

Figure 4. Oil prices diverged from other commodities in late 2014. Regression of oil prices on the prices of metals and agricultural commodities (monthly, 2001M1-2015M6)

We arrive at the same conclusion when studying the relationship between oil supply (quantities) and prices. A positive correlation between quantities and prices is suggestive of demand shocks and a negative one is suggestive of supply shocks. More formally, we regress a simple supply equation of the quantities of oil supplied on oil prices controlling (two-stage estimation) for global demand by using the measure (first principle component) we derived above. This allows us to identify supply shocks.7 Taking the results with appropriate caution (Figure 5), we note that recently, oil production has increased by 3% beyond what demand would have warranted.8

To conclude, our results indicate that the decline in oil prices reflects both a decline in global demand for goods and a large positive supply shock in the oil industry.

Oil prices and five-year expected inflation

We now proceed to test for the relationship between oil prices and expected inflation. We estimated a regression of five-year breakeven inflation rates on oil prices, allowing for a different effect before and after the Global Crisis.9 Similarly to the correlations reported in Table 1, the regression results (Figure 6) show a strengthening of the relationship between oil prices and medium-term inflation expectations after the onset of the Global Crisis. In fact, in all four cases we cannot reject the hypothesis that prior to the Global Crisis, oil prices and breakeven rates were uncorrelated.

In order to capture the forces that drive global inflation expectations and examine the effects of oil prices on these forces, we extracted the first principal component of five-year breakeven inflation rates from the US, the Eurozone, Israel, and the UK. As is apparent in Figure 7, this factor is highly correlated with the first principal component of commodity indices, suggesting a high correlation between expected inflation and global demand.

In order to estimate the extent to which the global demand embedded in oil prices affects expected inflation, we decomposed oil prices in two elements: one capturing global demand effects; and the other capturing idiosyncratic supply effects.10 A regression of the first principal component of inflation expectations on decomposed oil price changes reveals a similar picture to the one portrayed in Figure 6. While prior to the Global Crisis neither type of change in oil prices was significantly correlated with inflation expectations, from the onset of the Crisis both types of changes have been significantly correlated. In Table 3 we derive the country-specific elasticities of oil supply changes on inflation expectations.11

We conclude that the tightening relationship between oil prices and inflation expectations reflects a tightening relationship between global demand and medium term inflation expectations, as well as an increased effect of idiosyncratic supply shocks to oil on inflation expectations.

Monetary policy implications

Before the Global Crisis oil prices were not correlated with five-year expected inflation. During the Crisis, we saw that global demand and supply conditions reflected in oil prices became strongly correlated with inflation expectations. Examining the contribution of these factors (Figure 8) reveals that while both factors contribute more to the developments in inflation expectations, since the onset of the Crisis, global demand has a more dominant effect.12

In fact, it seems that in the post-crisis period, global demand explains a substantial part of the development in global expected inflation.

Figure 8. The contribution of global demand shocks to expected inflation is much higher than that of oil supply shocks (monthly, 2005M1-2015M6)

What can explain this change? We offer two possible, mutually non-exclusive, explanations:

The first is a change in monetary policy.

Before the Global Crisis, monetary authorities followed, or were expected to follow, a Taylor rule that puts a large weight on meeting the inflation target and little weight on stabilising output. Afterwards, monetary authorities were more concerned with stabilising the output (or employment) gap. It could be that the public interpreted this as a decline in the commitment to uphold the inflation target in the medium term. A variant of this explanation is that when inflation deviates below the target, the public believes that monetary authorities will be less aggressive in attempting to move it back into the target zone.

The second explanation is that because interest rates have reached the zero lower bound, the public doubts the ability of monetary authorities to meet the inflation target.[13]

Some questions remain. Did inflation targeting become unanchored in the medium term? If this is the case, has future stabilisation of inflation become more costly (until the public learns that weight has shifted again to inflation)? Has the credibility of the monetary regime declined?

Authors’ note: The views expressed in this note do not reflect the views of the Bank of Israel or its Monetary Policy Committee.

World Bank (2015), Global Economic Prospects, January 2015: Having Fiscal Space and Using It, Washington DC: World Bank, Chapter 4.

References

1 For the Eurozone, we used a GDP-weighted average of separately estimated breakeven rates for France and Germany. In many economies the market for indexed bonds is too thin.

2 The correlation in levels is above 80%. However, since we are ultimately interested in the effect on inflation, we report the annual rate of change.

3 The loadings on the first principal component are 0.61, 0.55, and 0.57 for oil, metals, and agricultural commodities, respectively. It is therefore clear that the principal component captures a common factor of these commodities and is not dominated by oil price changes. Furthermore, the principal component is highly correlated with IMF's estimates of global GDP and trade volume (correlations above 0.8).

4 A similar approach was taken in Byrne et al. (2013). They constructed a common factor of asset prices based on low-frequency data and examined variables that affect co-movements in asset prices. We construct a high-frequency common factor of prices and use it as an explanatory variable for oil prices and inflation expectations.

5 We controlled for shocks to oil demand by including weather conditions in the US. Details regarding the regression's specification and outputs can be found in the full version of the article.

6 Interestingly, we find that after controlling for weather conditions, the elasticity of oil prices with respect to other commodity prices is about 0.5. This implies that the oil cartel smooths oil prices relative to the behavior of other commodities.

7 We controlled for idiosyncratic demand shocks to oil using weather conditions in the US. Details regarding the regression's specification and outputs can be found in the full version of the paper.

8 Similar conclusions are derived in GEP, January 2015.

9 Detailed specifications of these regressions are given in the full version of the paper.

10 The decomposition was conducted with a regression of oil prices on the first principal component of commodity indices. The fitted value from this regression represents the part of oil price affected by global demand, while the residual represents the part affected by supply. (To be more precise, the residual represents supply effects on oil prices as well as idiosyncratic demand effects. We controlled for the latter using weather conditions in the US.)

11 Details regarding the estimation procedure and outputs are given in the full version of the paper.

12 The contributions were calculated as the size of each shock multiplied by the estimated marginal effect of that shock on the principal component of breakeven rates.